I love spreadsheets. Spreadsheet programs like Microsoft's Excel, Apple's Numbers and Google Sheets are the secret heroes of our civilization.

I've also been interested in personal finance and the FIRE community for a while—not so much in the early retirement aspect but in the financial literacy it teaches its members. I have combined my passion for both into one mega-spreadsheet that I use to track my income, expenses, savings and investments in one overview. While creating this spreadsheet I got proficient in some new formulas, which I'll share here—and also write down for my own reference.

In Boston they just did a poll where they asked "even though it means less space on the streets for cars, do you want to keep the parklets we've put in during COVID?" Eighty-one percent said keep the parklets. They asked about keeping the bike lanes and 79 percent said keep the bike lanes. This is a randomized poll, they're not stopping cyclists on the street. That's where public opinion is, but that's not necessarily what the leaders are hearing whenever the question comes up about keeping or eliminating an individual parklet or bike lane.

With several thousand characters to contend with, how were the Japanese able to use typewriters before the advent of digital technology? The answer is the kanji typewriter (和文タイプライター or 邦文タイプライター), which was invented by Kyota Sugimoto in 1915. This invention was deemed so important that it was selected as one of the ten greatest Japanese inventions by the Japanese Patent Office during their 100th anniversary celebrations in 1985. Here are some photos of that first model. (Photos courtesy Canon Semiconductor Equipment.)

Suppose we want to combine a BERT-based named entity recognition (NER) model with a rule-based NER model built on top of spaCy. Although BERT's NER exhibits extremely high performance, it is usually combined with rule-based approaches for practical purposes. In such cases, what often bothers us is that tokens of spaCy and BERT are different, even if the input sentences are the same. For example, let's say the input sentence is "John Johanson 's house"; BERT tokenizes this sentence like ["john", "johan", "##son", "'", "s", "house"] and spaCy tokenizes it like ["John", "Johanson", "'s", "house"]. To combine the outputs, we need to calculate the correspondence between the two different token sequences. This correspondence is the "alignment".

One conspiracy site even claimed vaccinated people were dying at higher rates than those who had not received the jab, which is untrue.

This site and others use real figures in a misleading way, to arrive at a completely false conclusion - that the vaccine may not be working or even doing more harm than good.

Are you prepared to receive and process privacy access requests in compliance with the GDPR? The following guide will help you understand your role in promoting access to data and how to create a system that saves you time and prevents damage to your reputation.

Any book of Why We Sleep's length is bound to contain some factual errors. Therefore, to avoid potential concerns about cherry-picking the few inaccuracies scattered throughout, in this essay, I'm going to highlight the five most egregious scientific and factual errors Walker makes in Chapter 1 of the book. This chapter contains 10 pages and constitutes less than 4% of the book by the total word count.

Audio on Unix is a little zoo, there are so many acronyms for projects and APIs that it's easy to get lost. Let's tackle that issue! Most articles are confusing because they either use audio technical jargon, or because they barely scratch the surface and leave people clueless. A little knowledge can be dangerous.

In this article I'll try to bridge the gap by not requiring any prerequisite knowledge while also giving a good overview of the whole Unix audio landscape. There's going to be enough details to remove mysticism (Oh so pernicious in web bubbles) and see how the pieces fit.

This is a different way to learn about crypto than taking a class or reading a book. We give you problems to solve. They're derived from weaknesses in real-world systems and modern cryptographic constructions. We give you enough info to learn about the underlying crypto concepts yourself. When you're finished, you'll not only have learned a good deal about how cryptosystems are built, but you'll also understand how they're attacked.

An open source research project exploring the role of machine learning as a tool in the creative process.

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